Matthew G. Bakker

Root Exudation of Phytochemicals in Arabidopsis Follows Specific Patterns That Are Developmentally Programmed and Correlate with Soil Microbial Functions

Plant roots constantly secrete compounds into the soil to interact with neighboring organisms presumably to gain certain functional advantages at different stages of development. Accordingly, it has been hypothesized that the phytochemical composition present in the root exudates changes over the course of the lifespan of a plant. Here, root exudates of in vitro grown Arabidopsis plants were collected at different developmental stages and analyzed using GC-MS. Principle component analysis revealed that the composition of root exudates varied at each developmental stage. Cumulative secretion levels of sugars and sugar alcohols were higher in early time points and decreased through development. In contrast, the cumulative secretion levels of amino acids and phenolics increased over time. The expression in roots of genes involved in biosynthesis and transportation of compounds represented in the root exudates were consistent with patterns of root exudation. Correlation analyses were performed of the in vitro root exudation patterns with the functional capacity of the rhizosphere microbiome to metabolize these compounds at different developmental stages of Arabidopsis grown in natural soils. Pyrosequencing of rhizosphere mRNA revealed strong correlations (p<0.05) between microbial functional genes involved in the metabolism of carbohydrates, amino acids and secondary metabolites with the corresponding compounds released by the roots at particular stages of plant development. In summary, our results suggest that the root exudation process of phytochemicals follows a developmental pattern that is genetically programmed.

Harnessing the rhizosphere microbiome through plant breeding and agricultural management

BackgroundThe need to enhance the sustainability of intensive agricultural systems is widely recognized One promising approach is to encourage beneficial services provided by soil microorganisms to decrease the inputs of fertilizers and pesticides. However, limited success of this approach in field applications raises questions as to how this might be best accomplished.ScopeWe highlight connections between root exudates and the rhizosphere microbiome, and discuss the possibility of using plant exudation characteristics to selectively enhance beneficial microbial activities and microbiome characteristics. Gaps in our understanding and areas of research that are vital to our ability to more fully exploit the soil microbiome for agroecosystem productivity and sustainability are also discussed.ConclusionThis article outlines strategies for more effectively exploiting beneficial microbial services on agricultural systems, and cals attention to topics that require additional research.

A Coevolutionary Framework for Managing Disease-Suppressive Soils

This review explores a coevolutionary framework for the study and management of disease-suppressive soil microbial communities. Because antagonistic microbial interactions are especially important to disease suppression, conceptual, theoretical, and empirical work on antagonistic coevolution and its relevance to disease suppression is reviewed. In addition, principles of coevolution are used to develop specific predictions regarding the drivers of disease-suppressive potential in soil microbial communities and to highlight important areas for future research. This approach brings an evolutionary perspective to microbial community management and emphasizes the role of species interactions among indigenous nonpathogenic microbes in developing and maintaining disease-suppressive activities in soil.

Potential impact of soil microbiomes on the leaf metabolome and on herbivore feeding behavior

It is known that environmental factors can affect the biosynthesis of leaf metabolites. Similarly, specific pairwise plant-microbe interactions modulate the plants metabolome by stimulating production of phytoalexins and other defense-related compounds. However, there is no information about how different soil microbiomes could affect the plant growth and the leaf metabolome. We analyzed experimentally how diverse soil microbiomes applied to the roots of Arabidopsis thaliana were able to modulate plant growth and the leaf metabolome, as assessed by GC-MS analyses. Further, we determined the effects of soil microbiome-driven changes in leaf metabolomics on the feeding behavior of Trichopulsia ni larvae. Soil microbiomes differentially impacted plant growth patterns as well as leaf metabolome composition. Similarly, most microbiome-treated plants showed inhibition to larvae feeding, compared with unamended control plants. Pyrosequencing analysis was conducted to determine the soil microbial composition and diversity of the soils used in this study. Correlation analyses were performed to determine relationships between various factors (soil microbial taxa, leaf chemical components, plant growth patterns and insect feeding behavior) and revealed that leaf amino acid content was positively correlated with both microbiome composition and insect feeding behavior.

Streptomyces competition and co-evolution in relation to plant disease suppression

High densities of antagonistic Streptomyces are associated with plant disease suppression in many soils. Here we review use of inoculation and organic matter amendments for enriching antagonistic Streptomyces populations to reduce plant disease and note that effective and consistent disease suppression in response to management has been elusive. We argue that shifting the focus of research from short-term disease suppression to the population ecology and evolutionary biology of antagonistic Streptomyces in soil will enhance prospects for effective management. A framework is presented for considering the impacts of short- and long-term management on competitive and coevolutionary dynamics among Streptomyces populations in relation to disease suppression.

Diffuse symbioses: roles of plant–plant, plant–microbe and microbe–microbe interactions in structuring the soil microbiome

A conceptual model emphasizing direct host–microbe interactions has dominated work on host‐associated microbiomes. To understand plant–microbiome associations, however, broader influences on microbiome composition and functioning must be incorporated, such as those arising from plant–plant and microbe–microbe interactions. We sampled soil microbiomes associated with target plant species (Andropogon gerardii, Schizachyrium scoparium, Lespedeza capitata, Lupinus perennis) grown in communities varying in plant richness (1‐, 4‐, 8‐ or 16‐species). We assessed Streptomyces antagonistic activity and analysed bacterial and Streptomyces populations via 454 pyrosequencing. Host plant species and plant richness treatments altered networks of coassociation among bacterial taxa, suggesting the potential for host plant effects on the soil microbiome to include changes in microbial interaction dynamics and, consequently, co‐evolution. Taxa that were coassociated in the rhizosphere of a given host plant species often showed consistent correlations between operational taxonomic unit (OTU) relative abundance and Streptomyces antagonistic activity, in the rhizosphere of that host. However, in the rhizosphere of a different host plant species, the same OTUs showed no consistency, or a different pattern of responsiveness to such biotic habitat characteristics. The diversity and richness of bacterial and Streptomyces communities exhibited distinct relationships with biotic and abiotic soil characteristics. The rhizosphere soil microbiome is influenced by a complex and nested array of factors at varying spatial scales, including plant community, plant host, soil edaphics and microbial taxon and community characteristics.

Effects of plant host species and plant community richness on streptomycete community structure

We investigated soil streptomycete communities associated with four host plant species (two warm season C4 grasses: Andropogon gerardii, Schizachyrium scoparium and two legumes: Lespedeza capitata, Lupinus perennis), grown in plant communities varying in species richness. We used actinobacteria-selective PCR coupled with pyrosequencing to characterize streptomycete community composition and structure. The greatest pairwise distances between communities were observed in contrasts between monocultures of different plant species, indicating that plant species exert distinct selective effects on soil streptomycete populations. Increasing plant richness altered the composition and structure of streptomycete communities associated with each host plant species. Significant relationships between plant community characteristics, soil edaphic characteristics, and streptomycete community structure suggest that host plant effects on soil microbial communities may be mediated through changes to the soil environment. Co-occurring streptomycete taxa also shared consistent relationships with soil edaphic properties, providing further indication of the importance of habitat preference for taxon occurrence. Physical distance between sampling points had a significant influence on streptomycete community similarity. This work provides a detailed characterization of soil streptomycete populations across a field scale and in relation to plant host identity and plant community richness.

Impacts of bulk soil microbial community structure on rhizosphere microbiomes of Zea mays

Background and aimsIt has frequently been shown that plants interact with soils to shape rhizosphere microbiomes. However, previous work has not distinguished between effects of soil properties per se, and effects attributable to the resident microbial communities of those soils. We aimed to test whether differences in the structure of bulk soil microbial communities, within a given soil type, would carry over to impact the structure of the rhizosphere microbial community.MethodsWe used repeated chemical amendments to develop divergent bulk soil microbial community starting points from which rhizosphere development proceeded. Additionally, we contrasted rhizosphere microbiomes associated with two different cultivars of corn (Zea mays).ResultsA wide range of bacterial and archaeal taxa responded to chemical resource amendments, which reduced bulk soil microbiome diversities. Corn genotypes P9714XR and 35F40 had largely similar impacts on rhizosphere microbiome development, although significant differences were evident in select treatments. Notably, in cases where resource amendments altered bulk soil microbial community composition, legacy effects persisted into the rhizosphere.ConclusionsOur results suggest that rhizosphere microbial communities may develop into different states depending on site history and prior selective events. This work advances our understanding of soil microbiome dynamics and responsiveness to change in the form of simple resource amendments and the development of the rhizosphere.

Subinhibitory Antibiotic Concentrations Mediate Nutrient Use and Competition among Soil Streptomyces

Though traditionally perceived as weapons, antibiotics are also hypothesized to act as microbial signals in natural habitats. However, while subinhibitory concentrations of antibiotics (SICA) are known to shift bacterial gene expression, specific hypotheses as to how SICA influence the ecology of natural populations are scarce. We explored whether antibiotic ‘signals’, or SICA, have the potential to alter nutrient utilization, niche overlap, and competitive species interactions among Streptomyces populations in soil. For nine diverse Streptomyces isolates, we evaluated nutrient utilization patterns on 95 different nutrient sources in the presence and absence of subinhibitory concentrations of five antibiotics. There were significant changes in nutrient use among Streptomyces isolates, including both increases and decreases in the capacity to use individual nutrients in the presence vs. in the absence of SICA. Isolates varied in their responses to SICA and antibiotics varied in their effects on isolates. Furthermore, for some isolate-isolate-antibiotic combinations, competition-free growth (growth for an isolate on all nutrients that were not utilized by a competing isolate), was increased in the presence of SICA, reducing the potential fitness cost of nutrient competition among those competitors. This suggests that antibiotics may provide a mechanism for bacteria to actively minimize niche overlap among competitors in soil. Thus, in contrast to antagonistic coevolutionary dynamics, antibiotics as signals may mediate coevolutionary displacement among coexisting Streptomyces, thereby hindering the emergence of antibiotic resistant phenotypes. These results contribute to our broad understanding of the ecology and evolutionary biology of antibiotics and microbial signals in nature.

Implications of Pyrosequencing Error Correction for Biological Data Interpretation

There has been a rapid proliferation of approaches for processing and manipulating second generation DNA sequence data. However, users are often left with uncertainties about how the choice of processing methods may impact biological interpretation of data. In this report, we probe differences in output between two different processing pipelines: a de-noising approach using the AmpliconNoise algorithm for error correction, and a standard approach using quality filtering and preclustering to reduce error. There was a large overlap in reads culled by each method, although AmpliconNoise removed a greater net number of reads. Most OTUs produced by one method had a clearly corresponding partner in the other. Although each method resulted in OTUs consisting entirely of reads that were culled by the other method, there were many more such OTUs formed in the standard pipeline. Total OTU richness was reduced by AmpliconNoise processing, but per-sample OTU richness, diversity and evenness were increased. Increases in per-sample richness and diversity may be a result of AmpliconNoise processing producing a more even OTU rank-abundance distribution. Because communities were randomly subsampled to equalize sample size across communities, and because rare sequence variants are less likely to be selected during subsampling, fewer OTUs were lost from individual communities when subsampling AmpliconNoise-processed data. In contrast to taxon-based diversity estimates, phylogenetic diversity was reduced even on a per-sample basis by de-noising, and samples switched widely in diversity rankings. This work illustrates the significant impacts of processing pipelines on the biological interpretations that can be made from pyrosequencing surveys. This study provides important cautions for analyses of contemporary data, for requisite data archiving (processed vs. non-processed data), and for drawing comparisons among studies performed using distinct data processing pipelines.